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2020 | OriginalPaper | Chapter

6. Algorithms Simulate Evolution

Author : Klaus Mainzer

Published in: Artificial intelligence - When do machines take over?

Publisher: Springer Berlin Heidelberg

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Abstract

Information processing with computers and humans is reproduced with artificial or natural languages. They are only special cases of symbolic representation systems, which can also be specified for genetic information systems. Genetic languages, with their grammatical rules, represent molecular processes to generate molecular sequences with genetic meanings. The key to understanding these molecular languages is not us humans, but the molecular systems that make use of them. We humans with our kind of information processing are only at the beginning to decipher and understand these languages with their rules. The formal language and grammar theories, together with the algorithmic complexity theory, provide the first approaches.
For genetic information, the nucleic acid language with the alphabet of the four nucleotides and the amino acid language with the alphabet of the twenty amino acids are used. In the nucleic acid language, a hierarchy of different language layers can be distinguished, starting at the lowest level of the nucleotides with the basic symbols A, C, G, T or U to the highest level of the genes in which the complete genetic information of a cell is stored. Each intermediate language level consists of units of the previous language level and gives instructions for various functions such as, e.g., transcription or replication of sequences.

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Metadata
Title
Algorithms Simulate Evolution
Author
Klaus Mainzer
Copyright Year
2020
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-59717-0_6

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